A potentiometer jack adjustment method based on fuzzy compliant control algorithm

Abstract

This invention discloses a potentiometer jack adjustment method based on a fuzzy compliant control algorithm, relating to the field of airborne equipment debugging technology. The method includes the following steps: guiding a screwdriver into a resistance adjustment jack; using a force sensor to collect the force signal, force change rate, torque signal, and torque change rate of the screwdriver in contact with the resistance adjustment jack, and performing fuzzification processing to obtain fuzzy force signal, fuzzy force change rate, fuzzy torque signal, and fuzzy torque change rate; based on the fuzzy force signal, fuzzy force change rate, fuzzy torque signal, fuzzy torque change rate, and preset fuzzy control rules, performing fuzzy inference to obtain the screwdriver's step length vector and angle vector; and using the step length vector and angle vector, a robotic arm controls the screwdriver to adjust its position and attitude. This invention can actively adjust the screwdriver's position and attitude using information from a force sensor combined with a fuzzy compliant control algorithm, thereby avoiding jamming during the insertion process.

Description

Technical Field

[0001] This invention relates to the field of airborne equipment debugging technology, and in particular to a potentiometer jack adjustment method based on a fuzzy compliant control algorithm. Background Technology

[0002] The fly-by-wire computer is a crucial component of the aircraft flight control system. Each analog fly-by-wire computer has several circular potentiometers on its adjustment panel. During ground debugging of the aircraft flight control system, the resistance of the potentiometers needs to be manually adjusted by inserting a screwdriver into the potentiometer sockets. Due to the large number of potentiometers and the small size of the potentiometer sockets, manual adjustment is inefficient and inconsistent.

[0003] Chinese patent (application number CN202210319684.6, publication date March 15, 2024) discloses an automatic adjustment method for a telemetry computer potentiometer. This method involves sampling the overall image of the potentiometer adjustment panel using a vision module, employing linearization processing and coordinate system transformation to obtain the position of each potentiometer in the robotic arm's coordinate system, and then controlling a screwdriver at the front of the robotic arm to insert it into the potentiometer's resistance adjustment hole. However, due to factors such as screwdriver posture errors or inconsistent potentiometer adjustment holes, the screwdriver is prone to jamming when inserted into the adjustment hole, preventing further downward movement and thus hindering the potentiometer adjustment task.

[0004] Chinese patent (application number CN202411163477.1, publication date October 22, 2024) discloses an adaptive compliant control method for articulated industrial robots based on impedance learning. This method establishes an impedance control model describing the dynamic relationship between the force applied to the robot's end effector and its position. Impedance learning is used to update impedance parameters in real time based on the end effector position control error and the magnitude of the contact force, enabling control of the industrial robot's movement based on either the end effector position or the end effector contact force. However, this method cannot accurately provide a mathematical model to express the relationship between the contact force and the position error when a screwdriver in different poses is inserted into a potentiometer adjustment hole, resulting in dynamically changing contact forces.

[0005] Therefore, how to provide a potentiometer socket adjustment method based on fuzzy compliant control algorithm, which can actively adjust the screwdriver position by combining information from force sensor feedback with fuzzy compliant control algorithm, thereby avoiding jamming during the socket process, is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention proposes a potentiometer jack adjustment method based on a fuzzy compliant control algorithm, which aims to solve the technical problem that the above-mentioned traditional automatic adjustment method of electric transmission computer potentiometer is prone to jamming of the screwdriver inserted into the adjustment square hole, and thus cannot successfully complete the automatic adjustment of the potentiometer resistance value.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] This invention provides a potentiometer jack adjustment method based on a fuzzy compliant control algorithm, comprising the following steps:

[0009] Step 1: The vision system guides the screwdriver to be inserted into the resistance adjustment hole of the potentiometer. The force sensor collects the force signal, force change rate, torque signal and torque change rate when the screwdriver contacts the inner wall of the resistance adjustment hole.

[0010] Step 2: The collected force signal, force change rate, torque signal, and torque change rate are respectively subjected to fuzzification processing to obtain fuzzy force signal, fuzzy force change rate, fuzzy torque signal, and fuzzy torque change rate;

[0011] Step 3: Perform fuzzy inference based on the fuzzy force signal, the fuzzy force change rate, and the preset fuzzy control rules to obtain the step vector for adjusting the screwdriver position; perform fuzzy inference based on the fuzzy torque signal, the fuzzy torque change rate, and the preset fuzzy control rules to obtain the angle vector for adjusting the screwdriver attitude;

[0012] Step 4: Based on the step length vector and the angle vector, the robotic arm controls the screwdriver to adjust its position and orientation so that the screwdriver can be inserted into the resistance adjustment hole without obstruction.

[0013] The present invention discloses a potentiometer jack adjustment method based on a fuzzy compliant control algorithm. Based on existing equipment, it can design fuzzy control rules based on the fuzzy compliant control algorithm and combine information from force sensor feedback to determine the step size and angle of screwdriver adjustment without increasing additional hardware investment or significantly increasing the amount of computation. This avoids jamming during the jacking process, thereby reducing potentiometer damage and improving the working efficiency of the automatic adjustment system.

[0014] As a further improvement to the above technical solution, the force fuzzification steps are as follows: set the domain of discourse of the contact force between the screwdriver and the resistance adjustment hole of the potentiometer to [-1,1]; take negative, zero, and positive linguistic values ​​for description; use trigonometric functions for the membership function of the subset with zero; and use trapezoidal functions for the membership functions of the subset with negative and positive subsets.

[0015] The steps for fuzzifying the rate of change of force are as follows: set the domain of the rate of change of contact force between the screwdriver and the potentiometer's resistance adjustment hole to [-2,1]; use three linguistic values—negative, zero, and positive—for description; use five linguistic values—negative large, negative medium, negative small, positive small, and positive large; use trigonometric functions for the membership functions of subsets negative medium, negative small, and positive small, and use trapezoidal functions for the membership functions of subsets negative large and positive large.

[0016] As a further improvement to the above technical solution, the fuzzification steps for torque are as follows: set the domain of discourse for the contact torque between the screwdriver and the resistance adjustment hole of the potentiometer to [-0.1, 0.1]; use negative, zero, and positive linguistic values ​​for description; use trigonometric functions for membership functions of subsets with zero membership; and use trapezoidal functions for membership functions of subsets with negative and positive membership.

[0017] The steps for fuzzification of the contact torque change rate are as follows: set the domain of discourse for the contact torque change rate between the screwdriver and the potentiometer's resistance adjustment hole to [-2,1]; use three linguistic values—negative, zero, and positive—for description; use five linguistic values—negative large, negative medium, negative small, positive small, and positive large; use trigonometric functions for the membership functions of subsets negative medium, negative small, and positive small, and use trapezoidal functions for the membership functions of subsets negative large and positive large.

[0018] As a further improvement to the above technical solution, the fuzzification steps of the step size are as follows: the universe of discourse of the step size is set to [-0.14, 0.14]; seven language values ​​are taken: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large; and the membership functions are all trigonometric functions.

[0019] As a further improvement to the above technical solution, the fuzzification steps for the angle are as follows: set the domain of the angle to [-10, 10]; take seven language values: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large; and use trigonometric functions for the membership functions.

[0020] As a further improvement to the above technical solution, the fuzzy control rules adopt the form of if-and-then; the Mamdani method is selected as the fuzzy inference method. In the Mamdani method, the fuzzy relation generation rules are defined by taking the smaller value between sets, and the inference synthesis rules adopt the maximum-minimum synthesis method.

[0021] As a further improvement to the above technical solution, in step three, the centroid method is used to deblur the step length vector and the angle vector.

[0022] As a further improvement to the above technical solution, a visualization interface for fuzzy rules is obtained through the MATLAB Fuzzy Toolbox to verify the effectiveness of fuzzy control.

[0023] As a further improvement to the above technical solution, the fuzzy control rules include:

[0024] If the current contact force is in a negative direction and the rate of change of the force is negative, then the adjustment should be a moderate step size in the negative direction.

[0025] If the current contact force is in a negative direction and the rate of change of the force is negative, then the adjustment will be made in a smaller step in the negative direction.

[0026] If the current contact force is in a negative direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the negative direction.

[0027] If the current contact force is in a negative direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the negative direction.

[0028] If the current contact force is in a negative direction and the rate of change of the force is positive, then the adjustment will be a larger step in the negative direction.

[0029] If the current contact force is zero, the rate of change of force is not considered, and no further adjustment is made;

[0030] If the current contact force is in a positive direction and the rate of change of the force is negative, then the adjustment should be a moderate step size in the positive direction.

[0031] If the current contact force is in a positive direction and the rate of change of the force is negative, then the adjustment will be made in a smaller step in the positive direction.

[0032] If the current contact force is in a positive direction and the rate of change of the force is small and negative, then the adjustment should be a moderate step size in the positive direction.

[0033] If the current contact force is in a positive direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the positive direction.

[0034] If the current contact force is in a positive direction and the rate of change of the force is positive, then the adjustment will be a larger step in the positive direction.

[0035] As a further improvement to the above technical solution, the fuzzy control rules also include:

[0036] If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment should be to a moderate angle in the counterclockwise direction.

[0037] If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment will be to a smaller angle in the counterclockwise direction.

[0038] If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment should be a moderate angle in the counterclockwise direction.

[0039] If the current contact torque is counterclockwise and the rate of change of torque is small, then the adjustment should be a moderate angle in the counterclockwise direction.

[0040] If the current contact torque is counterclockwise and the rate of change of torque is positive, then the adjustment should be to a larger angle in the counterclockwise direction.

[0041] If the current contact torque is zero, the rate of change of torque is not considered and no further adjustment is made;

[0042] If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment should be to a moderate angle in the clockwise direction.

[0043] If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment will be to a smaller angle in the clockwise direction.

[0044] If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment should be a moderate angle in the clockwise direction.

[0045] If the current contact torque is clockwise and the rate of change of torque is small, then the adjustment should be a moderate angle in the clockwise direction.

[0046] If the current contact torque is clockwise and the rate of change of torque is positive, then the adjustment will be to a larger angle in the clockwise direction.

[0047] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a potentiometer jack adjustment method based on a fuzzy compliant control algorithm, which has the following advantages and beneficial effects:

[0048] 1. The potentiometer jack adjustment method based on the fuzzy compliant control algorithm of this invention, without increasing the investment in additional hardware equipment or significantly increasing the amount of computation, uses a fuzzy controller designed based on the fuzzy compliant control algorithm and combined with the information fed back from the force sensor to determine the step size and angle of screwdriver adjustment, avoiding jamming during the jacking process, reducing potentiometer damage, and improving the working efficiency of the automatic adjustment system.

[0049] 2. The potentiometer socket adjustment method based on the fuzzy compliant control algorithm of this invention uses the torque signal and torque change rate collected by the force sensor as input to obtain the angle vector as the basis for screwdriver posture adjustment. It can realize effective posture adjustment in complex situations of single-line contact and double-line contact between the screwdriver and the potentiometer resistance adjustment hole, and prevent jamming. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0051] Figure 1 A schematic diagram of the potentiometer jack adjustment device of the present invention;

[0052] Figure 2 A schematic diagram showing the installation state of the screwdriver and force sensor in the potentiometer jack adjustment device of the present invention;

[0053] Figure 3 A schematic diagram showing the surface contact state between the screwdriver and the resistance adjustment hole in the potentiometer jack adjustment device of the present invention;

[0054] Figure 4 A schematic diagram of a single-line contact state between the screwdriver and the resistance adjustment hole in the potentiometer jack adjustment device of the present invention;

[0055] Figure 5 A schematic diagram of the single-line contact two-state relationship between the screwdriver and the resistance adjustment hole in the potentiometer socket adjustment device of the present invention;

[0056] Figure 6 A schematic diagram showing the double-wire contact state between the screwdriver and the resistance adjustment hole in the potentiometer jack adjustment device of the present invention;

[0057] Figure 7 Structural block diagram of the position fuzzy controller of the present invention;

[0058] Figure 8 Structural block diagram of the attitude fuzzy controller of the present invention;

[0059] Figure 9 The membership function graph of force F in this invention;

[0060] Figure 10 The rate of change of force Δ in this invention F The membership function graph;

[0061] Figure 11 The membership function graph of the torque M in this invention;

[0062] Figure 12 The torque change rate Δ of this invention M The membership function graph;

[0063] Figure 13 The step size U of this invention S The membership function graph;

[0064] Figure 14 The invention's angle U A The membership function graph;

[0065] Figure 15 The rule observer of the position fuzzy controller of the present invention;

[0066] Figure 16 The rule observer of the attitude fuzzy controller of the present invention;

[0067] Figure 17 Input and output surface views of the position fuzzy controller of the present invention;

[0068] Figure 18 Input and output surface views of the attitude fuzzy controller of this invention;

[0069] In the diagram: 1. Base; 2. Robotic arm; 3. Screwdriver; 4. Force sensor; 5. Vision system; 51. Lens; 52. Camera; 53. Light source; 6. Host computer; 7. Potentiometer panel; 8. Potentiometer bracket; 9. Potentiometer; 91. Resistance adjustment hole. Detailed Implementation

[0070] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0071] In the description of this invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0072] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0073] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0074] According to embodiments of the present invention, such as Figure 1 and Figure 2 As shown, the potentiometer socket adjustment device includes: a base 1, a robotic arm 2, a screwdriver 3, a force sensor 4, a vision system 5, and a host computer 6. The robotic arm 2 is installed on one side of the base 1, and the potentiometer panel 7 is fixedly installed on the other side of the base 1 via a potentiometer bracket 8 and is horizontally aligned with the robotic arm 2. The force sensor 4 is installed at the end of the robotic arm 2, and the screwdriver 3 is installed at the tool connection end of the force sensor 4. The robotic arm 2, the vision system 5, and the force sensor 4 are all electrically connected to the host computer 6. The vision system 5 is used to collect the position information of the resistance adjustment holes of each potentiometer 9 on the potentiometer panel 7 in the coordinate system of the robotic arm 2 and send it to the host computer 6. The host computer 6 controls the screwdriver 3 to be inserted into the resistance adjustment hole 91 of the potentiometer 9 through the robotic arm 2.

[0075] Specifically, force sensor 4 is a six-axis force sensor; the FC-Medusa six-axis force sensor manufactured by BOTA in Switzerland can be selected. The force sensor 4 installed between the robotic arm 2 and the screwdriver 3 is used to detect the force and torque applied to the screwdriver 3 by the inner wall of the resistance adjustment hole 91 during the process of the screwdriver 3 being inserted into the resistance adjustment hole 91.

[0076] Specifically, the vision system 5 includes a lens 51, a camera 52, and a light source 53; the lens 51 is mounted on the front end of the camera 52, and the light source 53 is mounted on the end of the robotic arm 2. The camera 52 is electrically connected to the host computer 6.

[0077] Specifically, the process of inserting the screwdriver 3 into the resistance adjustment hole 91 of the potentiometer 9 is modeled and analyzed as follows:

[0078] Guided by the vision system 5, the robotic arm 2 controls the screwdriver 3 to complete the hole finding process, after which the screwdriver can be inserted into the resistance adjustment hole 91. However, due to factors such as errors in the screwdriver 3's posture or imperfect consistency of the resistance adjustment hole 91, three types of contact may occur between the screwdriver 3 and the inner wall of the resistance adjustment hole 91 during the insertion process: surface contact, single-line contact, and double-line contact. Figure 3 As shown, the contact between the screwdriver 3 and the resistor adjustment hole 91 is an ideal contact condition. In this case, the screwdriver 3 and the resistor adjustment hole 91 only have a lateral positional error, with no angular error. Figure 4 and Figure 5 As shown, both the screwdriver 3 and the resistor adjustment hole 91 are single-wire contacts. Single-wire contact has two types: one is single-wire contact type 1 (see...). Figure 4 Another type is single-line contact two (see...) Figure 5 In these two single-wire contact scenarios, there are positional and angular errors between the screwdriver 3 and the resistance adjustment hole 91. Figure 4 In the case of single-line contact, the force sensor experiences relatively little force along its four axes, and the screwdriver 3 can continue to move forward a certain distance. However, for... Figure 5 In the second scenario of single-line contact shown, screwdriver 3 cannot move forward further, resulting in a jamming phenomenon. For example... Figure 6 The diagram shows the screwdriver 3 in double-wire contact with the resistance adjustment hole 91. There are positional and angular errors between the screwdriver 3 and the resistance adjustment hole 91, causing the screwdriver to be unable to move downwards and resulting in a jamming phenomenon.

[0079] Specifically, for the design of the fuzzy control system, the fuzzy control system consists of two two-input, single-output controllers: a position fuzzy controller and an attitude fuzzy controller; the position fuzzy controller is as follows: Figure 7 As shown, the two inputs are the force F and the rate of change of force Δ collected by the force sensor, respectively. F , force change rate Δ F The defining formula is:

[0080]

[0081] In the formula F t F represents the current contact force. t-1 This represents the contact force before the last adjustment. The output is the step vector U. S The first system includes the direction and magnitude of movement; the second system, such as... Figure 8 As shown, the two inputs are the torque M and the rate of change of torque Δ collected by the force sensor. M Torque change rate Δ M The defining formula is:

[0082]

[0083] In the formula M t M represents the current torque. t-1 This represents the torque before the last adjustment. The output is an angle vector U. A It includes the direction and magnitude of rotation.

[0084] A potentiometer jack adjustment method based on a fuzzy compliant control algorithm includes the following steps:

[0085] Step 1: The vision system guides the screwdriver to be inserted into the potentiometer resistance adjustment hole. The force sensor collects the force signal, force change rate, torque signal and torque change rate when the screwdriver contacts the potentiometer resistance adjustment hole.

[0086] Step 2: The collected force signal, force change rate, torque signal, and torque change rate are fuzzified to obtain fuzzy force signal, fuzzy force change rate, fuzzy torque signal, and fuzzy torque change rate.

[0087] Step 3: Based on the fuzzy force signal, the fuzzy force change rate, and the preset fuzzy control rules, perform fuzzy inference to obtain the step vector for adjusting the screwdriver position; based on the fuzzy torque signal, the fuzzy torque change rate, and the preset fuzzy control rules, perform fuzzy inference to obtain the angle vector for adjusting the screwdriver attitude.

[0088] Step 4: Based on the step length vector and angle vector, the robotic arm controls the screwdriver to adjust its position and attitude so that the screwdriver can be inserted into the potentiometer socket without jamming.

[0089] In some embodiments, the input quantity is fuzzified, specifically as follows:

[0090] (1) Fuzziness of force

[0091] The direction of the force F collected by force sensor 4 determines the adjustment direction of screwdriver 3. F<0 indicates that the force direction is in the negative direction of the force sensor 4 coordinate axis; F>0 indicates that the force direction is in the positive direction of the force sensor 4 coordinate axis; F=0 indicates no force. Therefore, three linguistic values ​​are used to describe it: "negative (N)", "zero (ZO)", and "positive (P)". By observing force sensor 4, it is found that even in a static state, it still fluctuates between -0.3 and 0.3. That is to say, since force sensor 4 is very sensitive, there should be no force in the range of -0.3 to 0.3. Therefore, considering the fluctuation of the force data collected by force sensor 4, all values ​​of force F in a certain range near zero are classified as zero. Therefore, the membership function of subset ZO adopts a trigonometric function. If F<-1, the force is classified as -1, and if F>1, the force is classified as 1. Therefore, the membership functions of subsets N and P adopt a trapezoidal function, and the domain of discourse of the force is set to [-1,1]. The membership function graph of force F is shown below. Figure 9 As shown.

[0092] (2) Fuzzification of the rate of change of force

[0093] According to the rate of change of force Δ F As can be seen from the definition, when Δ F When Δ < 0, it indicates that the force decreased after adjustment. Specifically, when Δ F When Δ = -1, it indicates that the adjusted force is zero. FWhen Δ < -1, it indicates over-adjustment and a reversal of the force direction; when Δ F When Δ = 0, it indicates that the force remains unchanged after adjustment; when Δ = 0, it indicates that the force remains unchanged after adjustment. F When c > 0, it indicates that the force increases after adjustment, meaning the adjustment direction is incorrect. Specifically, when c = 1, it indicates that the force after adjustment is twice the force before adjustment. Therefore, the domain of the rate of change of force is set to [-2, 1], taking five linguistic values: "negative large (NB)", "negative medium (NM)", "negative small (NS)", "positive small (PS)", and "positive large (PB)". The membership functions of subsets NM, NS, and PS use trigonometric functions, while the membership functions of subsets NB and PB use trapezoidal functions. The rate of change of force Δ... F The membership function graph is as follows Figure 10 As shown.

[0094] (3) Fuzziness of torque

[0095] The direction of the torque M collected by force sensor 4 determines the orientation adjustment direction of screwdriver 3. M < 0 indicates a counterclockwise torque around the force sensor's coordinate axis; M > 0 indicates a clockwise torque around the force sensor's coordinate axis; M = 0 indicates no torque. Therefore, three linguistic values ​​are used to describe it: "negative (N)", "zero (ZO)", and "positive (P)". Since the torque data collected by force sensor 4 fluctuates, all values ​​of torque M within a certain range near zero are classified as zero. Therefore, the membership function of subset ZO uses a trigonometric function. If M < -0.1, the torque is classified as -0.1; if M > 0.1, the torque is classified as 0.1. Therefore, the membership functions of subsets N and P use a trapezoidal function, and the universe of discourse for the torque is set to [-0.1, 0.1]. The graph of the membership function of torque M is shown below. Figure 11 As shown.

[0096] (4) Fuzzification of the rate of change of torque

[0097] According to the rate of change of torque Δ M As can be seen from the definition, when Δ M When Δ < 0, it indicates that the torque has decreased after adjustment. Specifically, it is noted that when Δ M When Δ = -1, it indicates that the adjusted torque is 0; when Δ M When Δ < -1, it indicates over-adjustment, and the torque direction reverses. M When Δ = 0, it indicates that the torque has not changed after adjustment; when Δ = 0, it indicates that the torque has not changed after adjustment. M When Δ > 0, it indicates that the torque increases after adjustment. Specifically, it is noted that when Δ MWhen Δ = 1, it indicates that the adjusted torque is twice that before adjustment. Therefore, the domain of the rate of change of torque is set to [-2, 1], and five linguistic values ​​are taken: "negative large (NB)", "negative medium (NM)", "negative small (NS)", "positive small (PS)", and "positive large (PB)". The membership functions of subsets NM, NS, and PS are trigonometric functions, and the membership functions of subsets NB and PB are trapezoidal functions. The rate of change of torque Δ M The membership function graph is as follows Figure 12 As shown.

[0098] In some embodiments, the output is fuzzified, specifically as follows:

[0099] (1) Blurring of step size

[0100] In a positional fuzzy controller, the output is the step vector U. S The sign of the value indicates the direction of movement, and the magnitude indicates the step size. The domain of discourse for the step size is determined by the gap between the screwdriver 3 and the resistance adjustment hole 91, and is set to [-0.14, 0.14]. To make the step size adjustment more precise, seven linguistic values ​​are used: "Negative Large (NB)", "Negative Medium (NM)", "Negative Small (NS)", "Zero (ZO)", "Positive Small (PS)", "Positive Medium (PM)", and "Positive Large (PB)". The membership functions are all trigonometric functions, and the step size U S The membership function graph is as follows Figure 13 As shown.

[0101] (2) Blurring of angle

[0102] In the attitude fuzzy controller, the output is the angle vector U. A The sign of represents the direction of rotation, and its magnitude represents the rotation angle. Its domain is set to [-10, 10]. To allow for more precise angle adjustment, seven linguistic values ​​are used: "Negative Large (NB)", "Negative Medium (NM)", "Negative Small (NS)", "Zero (ZO)", "Positive Small (PS)", "Positive Medium (PM)", and "Positive Large (PB)". Trigonometric functions are used for all membership functions, and the angle U... A The membership function graph is as follows Figure 14 As shown.

[0103] It should be noted that the vertical axis of the membership function graph represents the membership degree, which describes the strength of an input variable belonging to a certain fuzzy set within a given range. The membership degree value ranges from 0 to 1. The horizontal axis represents different input variables.

[0104] In some embodiments, the knowledge base of fuzzy control rules is established with reference to the behavior of a person using a screwdriver 3 to insert a resistance adjustment hole 91 on the surface of a potentiometer 9, and its essence is a summary of practical experience and strategies.

[0105] For a positional fuzzy controller, the input force F has three linguistic values: the force change rate Δ. F There are five language values, and 15 control rules can be specified in the form of if-and-then, as shown in Table 1.

[0106] Table 1 Control Rules for Position Fuzzy Controller

[0107]

[0108] For an attitude fuzzy controller, the input torque M has three linguistic values, and the torque change rate Δ M There are five language values, and 15 control rules can be specified in the form of if-and-then, as shown in Table 2.

[0109] Table 2 Control Rules for Attitude Fuzzy Controller

[0110]

[0111] By combining the position fuzzy controller and the attitude fuzzy controller, the jamming phenomenon that occurs in the above three modeling scenarios can be avoided.

[0112] In some embodiments, fuzzy inference is uncertain inference that determines the output based on fuzzy relations and inputs. Considering the difficulty in establishing an accurate mechanical model for the process of inserting a screwdriver 3 into the resistance adjustment hole 91 on the surface of a potentiometer 9, and the need for rapid and efficient adjustment of the screwdriver 3's pose during insertion, the Mamdani method is chosen as the fuzzy inference method. In the Mamdani method, the fuzzy relation generation rules are defined by performing minimum operations between sets, and the inference synthesis rules adopt the maximum-minimum synthesis method.

[0113] In some embodiments, the centroid method uses the centroid of the area enclosed by the membership function curve and the horizontal axis as the output value. Compared to the maximum membership method, the centroid method has a smoother output and a more sensitive response. Even with small changes in the input, the output will change accordingly. The centroid method is suitable for deblurring processes with high precision requirements. Considering the high precision required for the screwdriver 3 to be inserted into the resistance adjustment hole 91 on the surface of the potentiometer 9, the centroid method is used for deblurring. The calculation formula for the centroid method is:

[0114]

[0115] Where x* is the value of the deblurred output; μ(x i ) represents the membership function, which is the probability that the output value falls within each region of the membership function; x i is the fuzzy output quantity; n is the number of fuzzy sets.

[0116] In some embodiments, fuzzy controller MATLAB simulations, based on the established membership functions of the inputs and outputs and fuzzy rules, can obtain a visual interface for the fuzzy rules through the MATLAB Fuzzy Toolbox. For example... Figure 15 The image shows a rule observer for a location fuzzy controller, such as... Figure 16 The diagram shows the rule observer for the attitude fuzzy controller. Operators can directly add input values ​​to the rule observer interface to obtain specific output values, facilitating direct verification of the fuzzy controller's effectiveness. For example... Figure 17 The image shows the input and output surface views of the positional fuzzy controller, with the two horizontal axes representing the input quantities F and Δ. F The vertical axis represents the output quantity U. S .like Figure 18 The image shows the input and output surface views of the attitude fuzzy controller, with the two horizontal axes representing the input quantities M and Δ. M The vertical axis represents the output quantity U. A The relationship between output and input can be visually observed through the input and output surface views. Figure 17 and 18 As can be seen, even with slight changes in the input, the output will change accordingly, which can meet the needs of the screwdriver to make slight adjustments to its position during the insertion process.

[0117] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0118] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A potentiometer jack adjustment method based on a fuzzy compliant control algorithm, characterized in that, Includes the following steps: Step 1: The vision system guides the screwdriver to be inserted into the resistance adjustment hole of the potentiometer. The vision system (5) is used to collect the position information of the resistance adjustment holes of each potentiometer (9) on the potentiometer panel (7) in the coordinate system of the robotic arm (2) and send it to the host computer (6). The host computer (6) controls the screwdriver (3) to be inserted into the resistance adjustment hole (91) of the potentiometer (9) through the robotic arm (2). The force sensor is used to collect the force signal, force change rate, torque signal and torque change rate when the screwdriver contacts the inner wall of the resistance adjustment hole. Step 2: The collected force signal, force change rate, torque signal, and torque change rate are respectively subjected to fuzzification processing to obtain fuzzy force signal, fuzzy force change rate, fuzzy torque signal, and fuzzy torque change rate; Step 3: Based on the fuzzy force signal, the fuzzy force change rate, and the preset fuzzy control rules, perform fuzzy inference to obtain the step vector used to adjust the screwdriver position; Based on the fuzzy torque signal, the fuzzy torque change rate, and the preset fuzzy control rules, fuzzy inference is performed to obtain the angle vector used to adjust the screwdriver's posture; Step 4: Based on the step length vector and the angle vector, the robotic arm controls the screwdriver to adjust its position and orientation so that the screwdriver can be inserted into the resistance adjustment hole without obstruction; The force fuzzification steps are as follows: set the domain of discourse of the contact force between the screwdriver and the potentiometer's resistance adjustment hole to [-1,1]; use negative, zero, and positive linguistic values ​​for description; use trigonometric functions for membership functions of subsets with zero membership; and use trapezoidal functions for membership functions of subsets with negative and positive membership. The fuzzification steps for the rate of change of force are as follows: set the domain of discourse for the rate of change of contact force between the screwdriver and the potentiometer's resistance adjustment hole to [-2,1]; use three linguistic values—negative, zero, and positive—for description; use five linguistic values—negative large, negative medium, negative small, positive small, and positive large; use trigonometric functions for the membership functions of subsets negative medium, negative small, and positive small, and use trapezoidal functions for the membership functions of subsets negative large and positive large. The fuzzification steps for torque are as follows: set the domain of discourse for the contact torque between the screwdriver and the potentiometer's resistance adjustment hole to [-0.1, 0.1]; use negative, zero, and positive linguistic values ​​for description; use trigonometric functions for membership functions of subsets with zero membership; and use trapezoidal functions for membership functions of subsets with negative and positive membership. The fuzzification steps for the contact torque change rate are as follows: set the domain of discourse for the contact torque change rate between the screwdriver and the potentiometer's resistance adjustment hole to [-2,1]; use three linguistic values—negative, zero, and positive—for description; use five linguistic values—negative large, negative medium, negative small, positive small, and positive large; use trigonometric functions for the membership functions of subsets negative medium, negative small, and positive small, and use trapezoidal functions for the membership functions of subsets negative large and positive large. The fuzzification steps for the step size are as follows: the universe of discourse for the step size is set to [-0.14, 0.14]; seven linguistic values ​​are selected: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large; and trigonometric functions are used for the membership functions. The steps for blurring the angle are as follows: set the universe of discourse of the angle to [-10, 10]; take seven linguistic values: negative large, negative medium, negative small, zero, positive small, positive medium, and positive large; and use trigonometric functions for the membership functions. Fuzzy control rules include: If the current contact force is in a negative direction and the rate of change of the force is negative, then the adjustment should be a moderate step size in the negative direction. If the current contact force is in a negative direction and the rate of change of the force is negative, then the adjustment will be made in a smaller step in the negative direction. If the current contact force is in a negative direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the negative direction. If the current contact force is in a negative direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the negative direction. If the current contact force is in a negative direction and the rate of change of the force is positive, then the adjustment will be a larger step in the negative direction. If the current contact force is zero, the rate of change of force is not considered, and no further adjustment is made; If the current contact force is in a positive direction and the rate of change of the force is negative, then the adjustment should be a moderate step size in the positive direction. If the current contact force is in a positive direction and the rate of change of the force is negative, then the adjustment will be made in a smaller step in the positive direction. If the current contact force is in a positive direction and the rate of change of the force is small and negative, then the adjustment should be a moderate step size in the positive direction. If the current contact force is in a positive direction and the rate of change of the force is small, then the adjustment should be a moderate step size in the positive direction. If the current contact force is in a positive direction and the rate of change of the force is large, then the adjustment will be a larger step in the positive direction. Fuzzy control rules also include: If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment should be to a moderate angle in the counterclockwise direction. If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment will be to a smaller angle in the counterclockwise direction. If the current contact torque is counterclockwise and the rate of change of torque is negative, then the adjustment should be a moderate angle in the counterclockwise direction. If the current contact torque is counterclockwise and the rate of change of torque is small, then the adjustment should be a moderate angle in the counterclockwise direction. If the current contact torque is counterclockwise and the rate of change of torque is positive, then the adjustment should be to a larger angle in the counterclockwise direction. If the current contact torque is zero, the rate of change of torque is not considered and no further adjustment is made; If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment should be to a moderate angle in the clockwise direction. If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment will be to a smaller angle in the clockwise direction. If the current contact torque is clockwise and the rate of change of torque is negative, then the adjustment should be a moderate angle in the clockwise direction. If the current contact torque is clockwise and the rate of change of torque is small, then the adjustment should be a moderate angle in the clockwise direction. If the current contact torque is clockwise and the rate of change of torque is positive, then the adjustment will be to a larger angle in the clockwise direction.

2. The potentiometer jack adjustment method based on fuzzy compliant control algorithm according to claim 1, characterized in that, The fuzzy control rules adopt the if-and-then form; the Mamdani method is selected as the fuzzy inference method. In the Mamdani method, the fuzzy relation generation rules are defined by taking the minimum value between sets, and the inference synthesis rules adopt the maximum-minimum synthesis method.

3. The potentiometer jack adjustment method based on fuzzy compliant control algorithm according to claim 2, characterized in that, In step three, the centroid method is used to deblur the step size vector and the angle vector.

4. The potentiometer jack adjustment method based on fuzzy compliant control algorithm according to claim 3, characterized in that, A visualization interface for fuzzy rules was obtained using the MATLAB Fuzzy Toolbox to verify the effectiveness of fuzzy control.

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